What this category of data looks like
Software development investment research data sources in the financial sector cover code repository commit records, API documentation, technical white papers, version change logs, test case spreadsheets, and technical presentation materials. Data update frequency fluctuates with development cycles. Core code and documentation are updated frequently with version iterations, while dependency lists and test reports are synced regularly during testing phases. Document formats include plain text Markdown, PDFs with code blocks, multi-sheet Excel files, PPTs with embedded vector images, and more. Fields include version numbers, commit IDs, function parameters, dependency library versions, and test case numbers. Units mostly use semantic version number format, bytes, and ISO standard time formats.
What constraints do these characteristics impose on document parsing and chunking?
Multi-source and heterogeneous software development investment research documents in the financial sector require parsing workflows to support cross-format adaptation, preventing loss of technical details due to format discrepancies. Frequently updated data requires parsing to support incremental synchronization, reducing resource consumption from repeated parsing. Complex document structures such as embedded code blocks, multi-sheet tables, and vector screenshots require chunking workflows to preserve original structures, avoiding damage to code logic and table hierarchies. Specific fields such as version numbers and commit IDs must be bound to corresponding content, ensuring retrieved results can be linked to specific development nodes. Additionally, software development documents often include code screenshots and rarely use pure text images, requiring flexible control over OCR trigger ranges.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
enable_pdf_ocr | Enable only when images contain printed text | Software development documents often include code screenshots and vector charts. OCR is not required for pure code images, which avoids generating garbled text |
split_mode | Split by semantic segments | Investment research documents contain technical logic and code blocks. Splitting by semantics preserves context integrity and avoids breaking code function descriptions |
excel_sheet_parse | Enable full sheet parsing | Software development test reports and dependency lists are often stored in multi-sheet files. Full parsing is required to extract all tab content fully, avoiding missing test case and dependency information |
max_chunk_length | 800–1200 characters | Balances the length of code blocks and technical descriptions. Prevents overly long chunks from breaking context, while controlling the retrieval granularity of individual chunks |
parse_image_skip | Skip OCR for .png/.svg format images | Software development documents mostly include vector images and code screenshots. OCR is not needed to restore these images, and retaining original files improves subsequent retrieval accuracy |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large code repository packaged documents takes significant time. Allocating sufficient processing time prevents parsing failures due to timeout |
The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After parsing a PDF containing code screenshots, the returned Markdown has no original images and only contains garbled text. Cause: The
parse_image_skipconfiguration to skip image OCR was not enabled, and forced text recognition was applied to all images, resulting in loss of original image resources. - Symptom: After parsing an Excel document, only the content of the first sheet is extracted, and test case and dependency information from other sheets are not included. Cause: The
excel_sheet_parseconfiguration was not enabled. The default setting only parses the first worksheet, which fails to cover content from multi-sheet software development documents. - Symptom: When importing a PPT or DOC document and enabling PDF enhanced parsing, the parsing result is empty or has incorrect formatting. Cause: PDF enhanced parsing only supports PDF format files. Non-PDF documents need to be switched to general parsing mode, otherwise content cannot be extracted normally.
How to confirm the configuration is correct
- Upload a test PDF containing code screenshots, and verify that the returned result retains the original images and has no garbled text generated by OCR.
- Upload a test Excel file with multiple sheets, and confirm that the parsing result covers content from all sheets with no missing tab information.
- Upload a test document in non-PDF format, switch to general parsing mode, and verify that the parsing result can normally extract text and structural information.
- View the detailed logs of the parsing task, and confirm that the actual effective values of the configuration items match the preset configurations, with no parameter conflicts.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.